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Bayesian statistical decision theory. --- Estadística bayesiana --- Bayes' solution --- Bayesian analysis --- Statistical decision --- Estadística de Bayes --- Fórmula de Bayes --- Presa de decisions (Estadística bayesiana) --- Solució de Bayes --- Teorema de Bayes --- Teoria de la decisió estadística bayesiana --- Presa de decisions

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Provides an accessible approach to Bayesian data analysis, as material is explained clearly with concrete examples. The book begins with the basics, including essential concepts of probability and random sampling, and gradually progresses to advanced hierarchical modeling methods for realistic data.

Mathematical statistics --- Bayesian statistical decision theory. --- R (Computer program language) --- GNU-S (Computer program language) --- Domain-specific programming languages --- Bayes' solution --- Bayesian analysis --- Statistical decision --- Bayesian statistical decision theory --- Estadística bayesiana --- R (Lenguaje de programación) --- GNU-S (Lenguaje de programación) --- Lenguajes de programación --- Análisis bayesiano --- Bayes, Solución de --- Bayes, Teorema de --- Decisión bayesiana, Teoría de la --- Inferencia bayesiana --- Solución de Bayes --- Teorema de Bayes --- Teoría de la decisión estadística bayesiana --- Toma de decisiones (Estadística bayesiana) --- Toma de decisiones --- Estadística bayesiana.

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Accessible to a variety of readers, this book is of interest to specialists, graduate students and researchers in mathematics, optimization, computer science, operations research, management science, engineering and other applied areas interested in solving optimization problems. Basic principles, potential and boundaries of applicability of stochastic global optimization techniques are examined in this book. A variety of issues that face specialists in global optimization are explored, such as multidimensional spaces which are frequently ignored by researchers. The importance of precise interpretation of the mathematical results in assessments of optimization methods is demonstrated through examples of convergence in probability of random search. Methodological issues concerning construction and applicability of stochastic global optimization methods are discussed, including the one-step optimal average improvement method based on a statistical model of the objective function. A significant portion of this book is devoted to an analysis of high-dimensional global optimization problems and the so-called ‘curse of dimensionality’. An examination of the three different classes of high-dimensional optimization problems, the geometry of high-dimensional balls and cubes, very slow convergence of global random search algorithms in large-dimensional problems , and poor uniformity of the uniformly distributed sequences of points are included in this book. .

Calculus of variations. --- Industrial engineering. --- Production engineering. --- Probabilities. --- Matrix theory. --- Algebra. --- Calculus of Variations and Optimal Control; Optimization. --- Industrial and Production Engineering. --- Probability Theory and Stochastic Processes. --- Linear and Multilinear Algebras, Matrix Theory. --- Mathematics --- Mathematical analysis --- Probability --- Statistical inference --- Combinations --- Chance --- Least squares --- Mathematical statistics --- Risk --- Manufacturing engineering --- Process engineering --- Industrial engineering --- Mechanical engineering --- Management engineering --- Simplification in industry --- Engineering --- Value analysis (Cost control) --- Isoperimetrical problems --- Variations, Calculus of --- Maxima and minima --- Nonconvex programming. --- Global optimization --- Non-convex programming --- Programming (Mathematics) --- Optimització matemàtica --- Estadística bayesiana --- Estadística de Bayes --- Fórmula de Bayes --- Presa de decisions (Estadística bayesiana) --- Solució de Bayes --- Teorema de Bayes --- Teoria de la decisió estadística bayesiana --- Presa de decisions --- Mètodes de simulació --- Jocs d'estratègia (Matemàtica) --- Optimització combinatòria --- Programació dinàmica --- Programació (Matemàtica) --- Anàlisi de sistemes

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Bayes Factors for Forensic Decision Analyses with R provides a self-contained introduction to computational Bayesian statistics using R. With its primary focus on Bayes factors supported by data sets, this book features an operational perspective, practical relevance, and applicability—keeping theoretical and philosophical justifications limited. It offers a balanced approach to three naturally interrelated topics: Probabilistic Inference - Relies on the core concept of Bayesian inferential statistics, to help practicing forensic scientists in the logical and balanced evaluation of the weight of evidence. Decision Making - Features how Bayes factors are interpreted in practical applications to help address questions of decision analysis involving the use of forensic science in the law. Operational Relevance - Combines inference and decision, backed up with practical examples and complete sample code in R, including sensitivity analyses and discussion on how to interpret results in context. Over the past decades, probabilistic methods have established a firm position as a reference approach for the management of uncertainty in virtually all areas of science, including forensic science, with Bayes' theorem providing the fundamental logical tenet for assessing how new information—scientific evidence—ought to be weighed. Central to this approach is the Bayes factor, which clarifies the evidential meaning of new information, by providing a measure of the change in the odds in favor of a proposition of interest, when going from the prior to the posterior distribution. Bayes factors should guide the scientist's thinking about the value of scientific evidence and form the basis of logical and balanced reporting practices, thus representing essential foundations for rational decision making under uncertainty. This book would be relevant to students, practitioners, and applied statisticians interested in inference and decision analyses in the critical field of forensic science. It could be used to support practical courses on Bayesian statistics and decision theory at both undergraduate and graduate levels, and will be of equal interest to forensic scientists and practitioners of Bayesian statistics for driving their evaluations and the use of R for their purposes. This book is Open Access.

Statistics. --- Mathematical statistics—Data processing. --- Forensic sciences. --- Medical jurisprudence. --- Forensic psychology. --- Social sciences—Statistical methods. --- Statistical Theory and Methods. --- Statistics and Computing. --- Forensic Science. --- Forensic Medicine. --- Forensic Psychology. --- Statistics in Social Sciences, Humanities, Law, Education, Behavorial Sciences, Public Policy. --- Juridical psychology --- Juristic psychology --- Legal psychology --- Psychology, Forensic --- Forensic sciences --- Psychology, Applied --- Forensic medicine --- Injuries (Law) --- Jurisprudence, Medical --- Legal medicine --- Medicine --- Medical laws and legislation --- Criminalistics --- Forensic science --- Science --- Criminal investigation --- Statistical analysis --- Statistical data --- Statistical methods --- Statistical science --- Mathematics --- Econometrics --- Bayes factor --- scientific evidence --- decision making --- forensic science --- uncertainty management --- probability theory --- forensic --- decision analysis --- Bayesian modeling --- R --- Bayesian statistics --- probabilistic inference --- Estadística bayesiana --- Processament de dades --- Criminalística --- R (Llenguatge de programació) --- GNU-S (Llenguatge de programació) --- Llenguatges de programació --- Ciències criminalístiques --- Ciències forenses --- Policia científica --- Policia tècnica --- Ciència --- Investigació criminal --- Economia forense --- Enginyeria forense --- Geologia forense --- Lingüística forense --- Psicologia forense --- Processament de dades electròniques --- Processament automàtic de dades --- Processament electrònic de dades --- Processament integrat de dades --- Sistematització de dades (Ordinadors) --- Tractament de dades --- Tractament electrònic de dades --- Tractament integrat de dades --- Automatització --- Informàtica --- Complexitat computacional --- Curació de dades --- Depuració (Informàtica) --- Estructures de dades (Informàtica) --- Gestió de bases de dades --- Informàtica mòbil --- Informàtica recreativa --- Intel·ligència artificial --- Sistemes en línia --- Temps real (Informàtica) --- Tractament del llenguatge natural (Informàtica) --- Processament òptic de dades --- Protecció de dades --- Transmissió de dades --- Tolerància als errors (Informàtica) --- Estadística de Bayes --- Fórmula de Bayes --- Presa de decisions (Estadística bayesiana) --- Solució de Bayes --- Teorema de Bayes --- Teoria de la decisió estadística bayesiana --- Presa de decisions

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This volume constitutes the refereed proceedings of the Second International Workshop on Advanced Methodologies for Bayesian Networks, AMBN 2015, held in Yokohama, Japan, in November 2015. The 18 revised full papers and 6 invited abstracts presented were carefully reviewed and selected from numerous submissions. In the International Workshop on Advanced Methodologies for Bayesian Networks (AMBN), the researchers explore methodologies for enhancing the effectiveness of graphical models including modeling, reasoning, model selection, logic-probability relations, and causality. The exploration of methodologies is complemented discussions of practical considerations for applying graphical models in real world settings, covering concerns like scalability, incremental learning, parallelization, and so on.

Computer Science --- Mechanical Engineering - General --- Mechanical Engineering --- Engineering & Applied Sciences --- Computer science. --- Computers. --- Algorithms. --- Mathematical statistics. --- Database management. --- Artificial intelligence. --- Computer Science. --- Artificial Intelligence (incl. Robotics). --- Algorithm Analysis and Problem Complexity. --- Probability and Statistics in Computer Science. --- Computation by Abstract Devices. --- Database Management. --- Information Systems Applications (incl. Internet). --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Data base management --- Data services (Database management) --- Database management services --- DBMS (Computer science) --- Generalized data management systems --- Services, Database management --- Systems, Database management --- Systems, Generalized database management --- Mathematics --- Statistical inference --- Statistics, Mathematical --- Statistics --- Probabilities --- Sampling (Statistics) --- Algorism --- Algebra --- Arithmetic --- Automatic computers --- Automatic data processors --- Computer hardware --- Computing machines (Computers) --- Electronic calculating-machines --- Electronic computers --- Hardware, Computer --- Computer systems --- Cybernetics --- Calculators --- Cyberspace --- Informatics --- Science --- Statistical methods --- Foundations --- Computer software. --- Artificial Intelligence. --- Software, Computer --- Application software. --- Application computer programs --- Application computer software --- Applications software --- Apps (Computer software) --- Computer software --- Intel·ligència artificial --- Estadística bayesiana --- Estadística de Bayes --- Fórmula de Bayes --- Presa de decisions (Estadística bayesiana) --- Solució de Bayes --- Teorema de Bayes --- Teoria de la decisió estadística bayesiana --- Presa de decisions --- Ciència cognitiva --- Mètodes de simulació --- Processament de dades --- Sistemes autoorganitzatius --- Aprenentatge automàtic --- Demostració automàtica de teoremes --- Intel·ligència artificial distribuïda --- Intel·ligència computacional --- Sistemes adaptatius --- Tractament del llenguatge natural (Informàtica) --- Raonament qualitatiu --- Representació del coneixement (Teoria de la informació) --- Sistemes de pregunta i resposta --- Traducció automàtica --- Visió per ordinador --- Xarxes neuronals (Informàtica) --- Xarxes semàntiques (Teoria de la informació) --- Agents intel·ligents (Programes d'ordinador) --- Programació per restriccions --- Vida artificial --- Intel·ligència artificial.